Prevalence of chronic kidney disease in Sri Lanka: A profile of affected districts reliant on groundwater
Bibliographic record
Abstract
This analysis provides new estimates of chronic kidney disease (CKD) prevalence - including CKD of unknown etiology (CKDu) - across ten districts most affected by CKD in Sri Lanka, including an examination of rural households' historical reliance on groundwater consumption. A carefully designed household survey provides information on whether these households self-reported having a member in the decade prior to 2018, who had been clinically diagnosed with CKD. Households were classified according to whether or not they had used groundwater (from household wells, agro-wells or springs) as their primary source for drinking or cooking for at least five years between 1999 and 2018. More than 98% of households reported having consumed groundwater as their primary source of drinking or cooking water for at least five of those years and >15% of households reported having at least one CKD-affected member in the ten-year period up to 2018, but these numbers varied across and within districts. The reported characteristics of symptomatic individuals reveal that the incidence of CKD was significantly higher among females (62%) than males (38%). In addition to CKD, about 63% of symptomatic individuals had hypertension and about one-third of them also had diabetes. About 33% of the symptomatic individuals had neither diabetes nor hypertension, where this group most closely fits commonly used definitions of CKDu. With a survey response of over 8000 households comprising as many as 30,000 individuals, these data illustrate the scale of CKD in the most-affected districts of Sri Lanka on an aggregate basis as well as revealing differences across districts and at the sub-district level.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".